The ability to detect and isolate rare target cells from heterogeneous samples is in high demand in cell biology research, immunology, tissue engineering and medicine. Techniques allowing label-free cell enrichment or detection would reduce the complexity and costs of clinical applications. Single-cell deformability has recently been recognized as a unique label-free biomarker for cell phenotype with implications for assessment of cancer invasiveness. Physical properties that define deformability include elasticity (Young's Modulus) for solid particles, and viscosity, viscosity ratio and surface tension for droplets.
Alteration in the deformability (or mechanical stiffness) of single cells has been identified to be a useful indicator of changes in cellular phenotype of importance for biological research. Various diseases are associated with cell deformability alterations including cancer, blood diseases (sickle cell anemia, hereditary spherocytosis, and immune hemolytic anemia), and inflammation. In particular, the stiffness of individual cancer cells has been found to be drastically reduced when compared to normal tissue of the same origin. Further, decreasing single-cell stiffness was correlated with increasing invasiveness or metastatic potential. Biomechanical assays confirmed this correlation both with in vitro human cancer cell lines as well as clinical biopsies. Moreover, pluripotent stem cells are more deformable than differentiated cells. Differentiated cells with different lineages will have different deformability. Cells that are responding to anti-cancer drugs have changes in deformability as well.
These results are practically important considering the simplicity and low potential cost for obtaining label-free biophysical measurements. A label-free deformability biomarker would likely have lower operating costs than current molecular-based biomarkers that require pre-processing steps, dyes, and/or costly antibodies. Furthermore, disease states of interest can be expanded to those without predetermined immunological markers as long as a correlation between deformability phenotype and clinical outcome is confirmed. Specifically, deformability-based target cell classification/enrichment would be useful for cancer research and diagnostics since it would enable controlled experiments correlating cell mechanics of cancer cell lines with known genetic defects as well as analysis of malignant cells of unknown origin (e.g. circulating tumor cells (“CTCs”) in peripheral blood or malignant cells in biopsy samples) for cancer staging, relapse detection, molecular analysis of cancer drug resistance, and potentially early detection.
In the short term, a simple point-of-care clinical device for enumeration of CTCs reduces the barrier for routine use. Identification of the number of CTCs in blood has been shown to be predictive of cancer prognosis and may suggest more or less aggressive treatment regimes. It also has potential for characterizing the efficacy of a particular chemotherapeutic therapy. Additionally, if genetic information about the primary tumor can be collected, this will allow non-invasive molecular biopsies of the primary cancer site that can indicate if the cancer is susceptible or has become resistant to specific drugs.
In the long term, isolation of populations of CTCs could allow molecular analysis to uncover new markers that are expressed in the unique deformable subset of tumor cells that may assist in diagnosis or understanding of the disease. In addition, if sensitivity and specificity is high enough, CTC analysis might make it possible to detect cancer early in pre-symptomatic patients or those who are at risk for relapse with a simple noninvasive blood test, leading to a decrease in cancer deaths.
Current techniques developed for measuring deformability and elastic properties of cells include micropipette aspiration, atomic force microscopy, optical deformability, magnetic bead twisting assays, and optical tweezers. Cell elastic constants (E) from 0.05-30 kPa have recently been measured by atomic force microscopy. Despite the success in obtaining overall deformability measurements for cells of interest, the low throughput (1 cell/min-1 cell/sec) of current cell deformability measurement techniques renders current technologies ill-suited for statistical analysis of large heterogeneous biological samples or rare cell detection. For example, current throughput does not allow routine screening of millions of cells, which is often desired for statistically robust diagnostic and research applications (e.g., detection/enumeration of cancer cells in blood or biopsies). Moreover, post-measurement enrichment of cell populations with uniform deformability has not been demonstrated for current technologies although high-purity isolation of viable cells with preserved gene expression profiles would facilitate the comprehensive assessment of single-cell mechanics correlated with unexplored genes responsible for such changes in phenotype. Further, many of these techniques are expensive because they are complicated or not passive.
Current techniques to isolate and enumerate rare cancer cells have shown promise for patient prognosis and treatment monitoring. In fact, the CTC detection system by Veridex Corp. was selected as the Top Medical Breakthrough for 2009 by the Cleveland Clinic. Unfortunately, current technologies have relatively low throughput (˜3-8 mL of blood/hr) and thus would be effective for early detection applications due to the very low number of CTCs in blood (<1 part per billion). Additionally, current techniques require immuno-labeling with magnetic beads and fluorescent markers which adds a large additional cost.
Novel techniques allowing deformability activated target cell/particle enrichment and/or high-throughput deformability measurement of individual cells would expand the research use and clinical adoption of this biomarker. Accordingly, there is a need for systems and methods for high-throughput deformability-based cell/particle categorization and sorting.